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Causal Inference Machine Learning Postdoctoral Jobs in Pasadena, CA

CookUnity

Director, Data Science/ML

Los Angeles, CA

Design and implement robust experimentation frameworks that enable rapid, high-quality product testing and learning * Develop causal inference methodologies to understand true incrementality of ...

Thrive Market

Senior Data Scientist

Los Angeles, CA · On-site +1

Design, build, and iterate on statistical models, machine learning systems, and decision frameworks ... causal inference, and interpretation of results. * Communicate insights, trade-offs, and ...

Paramount

Machine Learning Engineer

Burbank, CA · On-site

$109K - $143K/yr

Inference at Scale: Architecting the serving layer that handles billions of requests per day ... learning. * High-Performance Inference: Design and maintain K8s-based inference servers (e.g ...

Paramount

Machine Learning Engineer

Burbank, CA · On-site

$109K - $143K/yr

Inference at Scale: Architecting the serving layer that handles billions of requests per day ... learning. * High-Performance Inference: Design and maintain K8s-based inference servers (e.g ...

Voxelcloud

Machine Learning Engineer

Los Angeles, CA

Write production and deployment code (dockerization), iterate deployed models for optimal performance and inference speed * Conduct methodology research in deep learning to drive scalable, real-time ...

Voxelcloud

Machine Learning Engineer

Los Angeles, CA · On-site

Write production and deployment code (dockerization), iterate deployed models for optimal performance and inference speed * Conduct methodology research in deep learning to drive scalable, real-time ...

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All JobsCausal Inference Machine Learning Postdoctoral JobsCausal Inference Machine Learning Postdoctoral Jobs in Pasadena, CA

Causal Inference Machine Learning Postdoctoral information

See Pasadena, CA salary details

$38.7K

$59.1K

$66.5K

How much do causal inference machine learning postdoctoral jobs pay per year?

As of Jul 15, 2026, the average yearly pay for causal inference machine learning postdoctoral in Pasadena, CA is $59,147.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,400.00 and $61,600.00 per year, depending on experience, location, and employer.

What is a Causal Inference Machine Learning Postdoctoral researcher?

A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.

What are the key skills and qualifications needed to thrive as a Causal Inference Machine Learning Postdoctoral researcher, and why are they important?

To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.

What are some common challenges faced by Causal Inference Machine Learning Postdoctoral researchers when integrating causal models with real-world data?

Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.

What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.

What are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Pasadena, CA? For Causal Inference Machine Learning Postdoctoral jobs in Pasadena, CA, the most frequently searched job titles are:
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Pasadena, CA look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Pasadena, CA are:
What cities near Pasadena, CA are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities near Pasadena, CA with the most Causal Inference Machine Learning Postdoctoral job openings:
Causal Inference Machine Learning Postdoctoral jobs near you
Director, Data Science/ML

Director, Data Science/ML

CookUnity

Los Angeles, CA

Full-time

Medical, Vision, Retirement, PTO

Posted 10 days ago

Job description

About CookUnity:

Food has lost its soul to modern convenience. And with it, it has lost the power to nourish, inspire, and connect us. So in 2018, CookUnity was founded as the first-of-its-kind platform that connects the world with the source of truly great food: chefs. Today, CookUnity delivers 50 million meals a year from the industry's best chefs to homes all over the country. Fresh. Ready-to-eat. And crafted with the passion that nourishes body and soul.

Unwilling to stop there, CookUnity is expanding beyond delivery to become an ever-innovating marketplace focused on our singular mission: empower Chefs to nourish the world.

If that mission has you hungry in more ways than one, you've found the right job posting.

The role:

We're looking for a Director, Data Science/ML who will drive CookUnity's next phase of product innovation through forward-looking data science capabilities. This role goes beyond traditional analytics—you'll be responsible for building the ML and experimentation foundation that enables personalized, intelligent product experiences at scale.

You'll own the strategic vision for how data science shapes our product roadmap. You'll build and lead a team focused on predictive modeling, personalization, experimentation frameworks, and emerging ML capabilities that directly impact customer engagement, retention, and lifetime value. This is a high-impact role for someone who thinks strategically about the future of product science while remaining hands-on in driving technical execution.

Responsibilities:Strategic Vision & Product Partnership
  • Define and execute the product data science strategy, identifying opportunities where ML and predictive analytics can unlock step-change improvements in customer experience and business outcomes
  • Partner closely with Product, Growth, Engineering, and UX leadership to influence product roadmap with data-driven insights and forward-looking ML capabilities
  • Act as a thought leader on emerging data science techniques (personalization, recommendation systems, causal inference, generative AI) and their application to product problems
  • Translate complex product challenges into clear data science problems with measurable success criteria
  • Own the end-to-end ML lifecycle for product use cases: problem framing, feature development, model training, deployment, monitoring, and iteration
  • Partner with the Growth Data Science & Analytics team to align experimentation, measurement, and modeling efforts into a cohesive end-to-end data science ecosystem.
Team Leadership & Development
  • Build, mentor, and scale a high-performing product data science team capable of delivering both strategic insights and production ML systems
  • Foster a culture of innovation, experimentation, and continuous learning within the data science organization
  • Create career development pathways that attract and retain top data science talent
  • Collaborate with Analytics Engineering to ensure seamless model deployment and monitoring
Advanced Analytics & ML Capabilities
  • Own and evolve personalization and recommendation systems that drive engagement and conversion across the customer journey
  • Design and implement robust experimentation frameworks that enable rapid, high-quality product testing and learning
  • Develop causal inference methodologies to understand true incrementality of product changes.
  • Ensure models are observable, explainable where needed, and continuously improved post-launch
Product Measurement & Impact
  • Define product success metrics and measurement frameworks that align with business objectives
  • Build scalable dashboards and monitoring systems that provide real-time visibility into product performance
  • Conduct deep-dive analyses on user behavior patterns to uncover opportunities for product optimization
Qualifications:
  • 10+ years of experience in data science, with at least 5 years in leadership roles managing data scientists or ML engineers
  • Proven track record building and deploying ML models in production, particularly in personalization, recommendation systems, or predictive modeling
  • Deep expertise in experimentation and causal inference, including A/B testing, incrementality measurement, and statistical rigor
  • Strong product sense and business acumen—ability to identify high-impact opportunities and translate them into data science initiatives
  • Experience in consumer tech, e-commerce, or marketplace businesses where personalization and user engagement are critical
  • Excellent communication skills—ability to explain complex technical concepts to non-technical stakeholders and influence product strategy
  • Hands-on technical proficiency in Python, SQL, and modern ML frameworks (scikit-learn, PyTorch, TensorFlow)
  • Experience with cloud-based data infrastructure (AWS, GCP, Snowflake) and ML Ops tools (MLflow, Airflow, Kubeflow)
Preferred requirements:
  • PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field
  • Experience with real-time ML systems and feature stores
  • Background in recommendation systems or two-tower/multi-modal embeddings
  • Familiarity with generative AI and LLM applications in product contexts
  • Experience building data science teams from scratch or through periods of rapid growth
  • Prior work in subscription businesses or retention-focused products
  • Knowledge of modern product analytics tools (Amplitude, MixPanel, Looker)
What Success Looks Like
  • 6 months: Established product data science roadmap aligned with business priorities; shipped at least one high-impact ML model to production; built strong partnerships with Product and Engineering leadership
  • 12 months: Scaled the product data science function with key hires; delivered measurable improvements in personalization and customer engagement metrics; implemented robust experimentation frameworks used across product teams
Learn More About CookUnity

We believe great leadership starts with alignment on vision, values, and ways of working. To give you deeper insight into who we are and what we're looking for, we invite you to explore: CookUnity's Leadership Principles – The values and behaviors that guide how we operate, collaborate, and scale.

We hope this provides valuable insight into our culture and product vision. If this excites you, we'd love to connect!

Benefits

🩺 Health Insurance coverage

🌅 401k Plan

📈 We grow, you grow: Stock Options Plan granted on Day 1

🌟 Eligible for a bi-annual performance bonus

⛱ Unlimited PTO

🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical

🐣 Paid Family leave

🕯 Compassionate Leave: 3-5 days each time the need arises

🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly

🧘🏽‍♀️ Wellness perks: access to fitness subsidies to build a healthy lifestyle

🤖 AI-forward workplace: enterprise access to ChatGPT and Claude to help you work smarter and grow faster.

👩🏾‍🏫 Personalized Spanish coach

🚀 Awesome opportunity to join a company that is looking to change how we eat and how chefs work!

Compensation All final pay rates will be determined by candidates experience, knowledge, skills, and abilities of the applicant, internal equity, and alignment with market data.
Pay Range for this position
$240,000—$270,000 USD

If you're interested in this role, please submit your application, and if we think you might be a fit, we'll get in touch with you. Thank you for your time!

CookUnity is an Equal Opportunity Employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability.

A quick note for all candidates
We've recently seen an increase in recruitment scams across the industry, and we want to make sure you (and your data) stay safe while applying to CookUnity. We also want you to know that we take this seriously — sometimes, as part of our process, we may ask for a brief "proof of humanity" to confirm that we're connecting with a real person, not an impersonator. Here are a few tips to help you protect yourself and know what to expect from us:

  • Apply only through our official channels. All open roles are listed on our official careers page: careers.cookunity.com
  • Our recruiters are real people — and easy to verify. You can always find them on LinkedIn with verified profiles. If you're unsure, feel free to reach out to us on our official LinkedIn Company Page.
  • We only communicate through official CookUnity channels. That means emails ending in @cookunity.com and interviews held through official company platforms (Google Meet or Zoom) — never WhatsApp, Telegram, or SMS.
  • We'll never ask for payment or personal financial details. If anyone does, please don't share any information and let us know right away.

If something ever feels off or you're unsure about a message, we'd much rather you double-check with us. You can always contact us directly through any of our social media channels. We appreciate your interest in joining CookUnity — and we care about keeping your experience (and safety) as genuine as possible.